CN114624431A - Immunoassay analyzer and correction method thereof - Google Patents

Immunoassay analyzer and correction method thereof Download PDF

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CN114624431A
CN114624431A CN202210509978.5A CN202210509978A CN114624431A CN 114624431 A CN114624431 A CN 114624431A CN 202210509978 A CN202210509978 A CN 202210509978A CN 114624431 A CN114624431 A CN 114624431A
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control module
particle
clusters
range
detection data
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CN114624431B (en
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燕赛赛
方建伟
李国军
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Shenzhen Dymind Biotechnology Co Ltd
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/5302Apparatus specially adapted for immunological test procedures
    • GPHYSICS
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    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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    • G01N21/62Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/64Fluorescence; Phosphorescence
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    • G01N33/531Production of immunochemical test materials
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    • G01N33/53Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/543Immunoassay; Biospecific binding assay; Materials therefor with an insoluble carrier for immobilising immunochemicals
    • G01N33/54313Immunoassay; Biospecific binding assay; Materials therefor with an insoluble carrier for immobilising immunochemicals the carrier being characterised by its particulate form
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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Abstract

The application discloses an immunoassay analyzer and a correction method thereof, wherein the correction method comprises the following steps: the control module acquires the quantity of the items of the immune joint inspection and acquires the detection data from the detection module; the control module performs cluster grabbing processing on the detection data to obtain a plurality of clusters; the control module compares the quantity of all the particle clusters with the quantity of the items; and the control module judges that the number of the particle clusters is smaller than the number of the items, and corrects the particle clusters based on the median value of each particle cluster and the corresponding preset item range. By the method, the particle cluster can be corrected, and the accuracy is improved.

Description

Immunoassay analyzer and correction method thereof
Technical Field
The application relates to the technical field of blood sample analysis, in particular to an immunoassay analyzer and a correction method thereof.
Background
The existing immunoassay analyzer adopts microspheres to detect a sample, and the microspheres are easy to generate a polymerization phenomenon in the detection process, so that the particles of the sample are polymerized. Because the particles are polymerized, the detection items of the immunoassay analyzer have two particle clusters in the subsequent cluster grabbing process, and the accuracy of the immunoassay analyzer is low.
Disclosure of Invention
In order to solve the above problem, the present application provides a correction method, which is applied to an immunoassay analyzer, the immunoassay analyzer includes a detection module and a control module, the detection module is used for performing a plurality of detections of an immune joint test on a sample, and the correction method includes:
the control module acquires the quantity of the items of the immune joint inspection and acquires the detection data from the detection module;
the control module performs cluster grabbing processing on the detection data to obtain a plurality of clusters;
the control module compares the quantity of all the particle clusters with the quantity of the items;
and the control module judges that the number of the particle clusters is smaller than the number of the items, and corrects the particle clusters based on the median value of each particle cluster and the corresponding preset item range.
Wherein the detection data comprises forward scattered light detection data, side scattered light detection data and classified fluorescence detection data, and the step of the control module correcting the particle clusters based on the median value of each particle cluster and the corresponding preset item range comprises the following steps:
the control module acquires a first median value of each particle group on the forward scattered light and a second median value of each particle group on the classified fluorescence;
wherein the range of items includes a forward scattered light range and a classified fluorescence range corresponding to the particle cluster.
The step of the control module correcting the particle clusters based on the median value of each particle cluster and the corresponding preset item range comprises the following steps:
the control module judges whether the first median value is located in the corresponding forward scattering light range or not and whether the second median value is located in the corresponding classified fluorescence range or not;
if not, the control module acquires the particles in the item range as valid particles of the corresponding item so as to correct the particle cluster.
After the step of acquiring, by the control module, the particles within the item range as valid particles of the corresponding item, the correction method further includes:
and the control module stores the item range to the range array of the corresponding particle cluster.
The method for obtaining the particle clusters by the control module comprises the following steps of:
the control module selects any two of scattered light detection data, side scattered light detection data and classified fluorescence detection data to establish a scatter diagram.
After the step of selecting any two from the scattered light detection data, the side scattered light detection data and the classified fluorescence detection data by the control module to establish the scatter diagram, the correction method further comprises the following steps:
the control module performs Gaussian filtering, median filtering or mean filtering on the scatter diagram;
the control module carries out binarization on the filtered scatter diagram, carries out opening operation and acquires a communicated region to obtain a plurality of first particle clusters;
the control module obtains the range of each first particle cluster to obtain a corresponding range array.
Wherein the step of the control module comparing the number of all clusters with the number of items comprises:
the control module judges whether the number of the particle clusters is larger than the number of the items, and then the control module judges whether the median values of all the particle clusters are located in the same item range;
and the control module judges that the median of at least two particle clusters is in the same item range, and then the control module reserves the particle cluster with the largest area.
Wherein the step of the control module comparing the number of all clusters with the number of items comprises:
and the control module judges that the number of the particle clusters is equal to the number of the items, and the control module judges that the median of at least two particle clusters is in the same item range, so that the control module reserves the particle cluster with the largest area.
Wherein, the correction method further comprises:
the control module calculates corresponding fluorescence intensity based on the fluorescence channel corresponding to each particle group;
and the control module compares the fluorescence intensity with a preset calibration curve to obtain the item concentration corresponding to the particle cluster.
The application adopts another technical scheme that: the utility model provides an immunoassay appearance, immunoassay appearance includes detection module and control module, and detection module is used for carrying out the multiple detection of immune joint inspection to the sample, wherein:
the control module is used for acquiring the quantity of the items of the immune joint inspection and acquiring the detection data from the detection module;
the control module is used for carrying out cluster grabbing processing on the detection data to obtain a plurality of clusters;
the control module is used for comparing the quantity of all the particle clusters with the quantity of the items;
and the control module is used for judging that the number of the particle clusters is less than the number of the items, and correcting the particle clusters based on the median value of each particle cluster and the corresponding preset item range.
The immunoassay analyzer comprises a detection module and a control module, wherein the detection module is used for carrying out immunoassay joint inspection multiple items on a sample, the control module acquires the item quantity of immunoassay joint inspection, and the detection data are acquired from the detection module; the control module performs cluster grabbing processing on the detection data to obtain a plurality of clusters; the control module compares the quantity of all the particle clusters with the quantity of the items; and the control module judges that the number of the particle clusters is smaller than the number of the items, and corrects the particle clusters based on the median value of each particle cluster and the corresponding preset item range. The particle clusters are corrected through the control module based on the median value of each particle cluster and the corresponding and preset project range, the problem that the project in the prior art has two particle clusters can be solved, and the accuracy is improved.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts. Wherein:
FIG. 1 is a schematic flow chart diagram of a first embodiment of a correction method of the present application;
FIG. 2 is a schematic structural view of a first embodiment of the immunoassay analyzer of the present application;
FIG. 3 is a schematic diagram of a first scatter plot;
FIG. 4 is a schematic illustration of a plurality of clusters;
FIG. 5 is a schematic flow chart of a first embodiment of step S104 in FIG. 1;
FIG. 6 is a schematic illustration of a corrected cluster;
FIG. 7 is a schematic flowchart of a first embodiment of step S102 in FIG. 1;
fig. 8 is a schematic flow chart of a second embodiment of the modification method of the present application.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, embodiments accompanying the present application are described in detail below with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first", "second", etc. in this application are used to distinguish different objects, and are not used to describe a particular order. Furthermore, the terms "include" and "provided," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The immunoassay analyzer is a common medical instrument and is used for detecting various immunity indexes in a sample. Referring to fig. 1-2, fig. 1 is a schematic flow chart of a first embodiment of the correction method of the present application, and fig. 2 is a schematic structural diagram of a first embodiment of an immunoassay analyzer of the present application. The immunoassay analyzer of the embodiment comprises a detection module 11 and a control module 12, wherein the control module 12 is connected with the detection module 11, and the control module 12 is used for controlling the detection module 11 to perform a plurality of immunoassay joint tests on a sample; the sample may be serum or whole blood.
Optionally, the immunoassay analyzer further comprises a sample introduction module and a reaction module, the sample introduction module is configured to accommodate a sample and a reagent, and the reagent comprises at least one microsphere (e.g., magnetic bead); the reaction module is used for separating a sample and a reagent and the like to obtain a sample to be detected; the detection module 11 is used for detecting a sample to be detected to obtain detection data. The sample to be detected can be a magnetic bead compound, and the magnetic bead compound comprises magnetic beads, antigens, antibodies and fluorescent biotin combined on the antibodies; the antigen is from a sample. Different magnetic beads can be combined with different types of antigens in a sample to form different magnetic bead compounds, joint inspection operation (namely immune joint inspection of a plurality of items) of detecting various parameter indexes can be realized by inputting the sample into the same reaction cup once, the detection process is simple to operate, and the detection efficiency is high.
The correction method of the embodiment comprises the following steps:
s101: the control module 12 obtains the number of items of the immune joint inspection and obtains the inspection data from the inspection module 11.
The immunoassay analyzer is preset with items of the immune joint inspection, and the control module 12 counts the number of the items of the obtained immune joint inspection, namely the total number of the items detected by the immunoassay analyzer for one sample.
The detection module 11 is configured to detect magnetic bead complexes corresponding to different indexes, which are prepared from the same sample, to obtain detection data of the different indexes, so as to implement joint detection of multiple items of the same sample. Alternatively, different magnetic bead complexes may be formed by adding different magnetic beads or fluorescent biotin-labeled antibodies of different intensities, or the like.
The control module 12 obtains detection data from the detection module 11, which may include at least three dimensions of detection data. The at least three dimensions of the detection data may be three dimensions of detection data, the detection data including in particular forward scattered light (FSC) detection data, side scattered light (SSC) detection data, and Classified Fluorescence (CFL) detection data, wherein the Classified Fluorescence (CFL) detection data is used to distinguish between different items, the forward scattered light (FSC) detection data and the side scattered light (SSC) detection data being related to the size of the microspheres. In other embodiments, the at least three dimensions of detection data may be other dimensions of detection data, such as four dimensions of detection data or five dimensions of detection data.
Alternatively, the control module 12 establishes coordinates with the forward scattered light as an abscissa and the classified fluorescence as an ordinate, and projects the scattered light detection data and the classified fluorescence detection data in the detection data onto the coordinates to obtain a first scattergram, as shown in fig. 3.
S102: the control module 12 performs a cluster grasping process on the detection data to obtain a plurality of clusters.
The control module 12 performs a cluster grasping process on the detection data to obtain a plurality of clusters. In the process of detecting a sample by using the immunoassay analyzer, a phenomenon of particle aggregation may occur, which causes that the immunoassay analyzer in the prior art has two particle clusters in an item.
Alternatively, the control module 12 performs a blob processing on the detection data, that is, the control module 12 performs the blob processing on the first scatter diagram shown in fig. 3 to obtain a plurality of blobs on the coordinates, as shown in fig. 4.
S103: the control module 12 compares the number of all clusters with the number of items.
The control module 12 takes the number of all the clusters captured and compares the number of all the clusters with the number of items. The control module 12 determines that the number of clusters is smaller than the number of items, and then proceeds to step S104.
S104: if the control module 12 determines that the number of clusters is smaller than the number of items, the control module 12 corrects the clusters based on the median and the corresponding preset item range of each cluster.
If the control module 12 determines that the number of clusters is smaller than the number of items, the control module 12 corrects the clusters based on the median and the corresponding preset item range of each cluster. That is, the control module 12 sets a project range in advance, calculates a median value of each particle cluster, and corrects the particle cluster based on the median value of each particle cluster and the preset project range.
In this embodiment, the control module 12 corrects the particle clusters based on the median of each particle cluster and the corresponding and preset project range, so that the problem that the project in the prior art has two particle clusters can be solved, and the accuracy is improved.
Referring to fig. 5, fig. 5 is a schematic flowchart illustrating the first embodiment of step S104 in fig. 1. The step S104 includes the following steps:
s301: control module 12 obtains a first median value for each cluster of particles on the forward scattered light and a second median value on the classified fluorescence.
The control module 12 establishes a coordinate system with the forward scattered light as an abscissa and the classified fluorescence as an ordinate, and performs a bolus processing on the detection data to obtain a plurality of particle boluses as shown in fig. 4. The control module 12 obtains a first median of each particle group on the forward scattered light and a second median of each particle group on the classified fluorescence, for example, the first median is the median (or median) of each particle group on the forward scattered light, and the second median is the median (or median) of each particle group on the classified fluorescence.
The preset item range of the control module 12 includes a forward scattered light range and a classified fluorescence range corresponding to the particle cluster. That is, each particle group is provided with a forward scattered light range and a classified fluorescence range.
S302: control module 12 determines whether the first median is within the corresponding forward scatter range and the second median is within the corresponding classified fluorescence range.
The control module 12 compares the first median value with the corresponding forward scattered light range and the second median value with the corresponding classified fluorescence range, i.e. the first median value of the same particle mass is compared with the forward scattered light range of the particle mass.
If yes, the control module 12 determines that the first median is located in the corresponding forward scattering light range, and the second median is located in the corresponding classified fluorescence range, which is equivalent to that the item corresponds to a particle cluster, and the control module 12 does not need to correct the particle cluster.
If not, the control module 12 determines that the first median value is not located in the corresponding forward scattered light range, or/and the second median value is not located in the corresponding classified fluorescence range, then step S303 is performed.
S303: the control module 12 acquires particles within the range of the item as valid particles of the corresponding item to correct the particle cluster.
Control module 12 determines that the first median value is not within the corresponding forward scattered light range, or/and the second median value is not within the corresponding classified fluorescence range, i.e., control module 12 determines that the item has no corresponding valid particle. Therefore, the control module 12 acquires the particles within the range of the item as valid particles corresponding to the item to obtain a particle cluster corresponding to the item, thereby implementing the correction of the particle cluster.
Optionally, the control module 12 corrects a plurality of particle clusters to obtain a plurality of corrected particle clusters, as shown in fig. 6, the items of the immunoassay analyzer correspond to one particle cluster, so as to improve the accuracy.
S304: the control module 12 saves the project range to the range array of the corresponding cluster.
The control module 12 obtains the range array in the process of performing the cluster grasping processing on the detection data, so that the control module 12 stores the project range to the corresponding range array of the particle cluster to correct the range array and improve the accuracy of the immunoassay analyzer.
In this embodiment, the control module 12 determines whether the first median is located in the corresponding forward scattering light range, and whether the second median is located in the corresponding classified fluorescence range; if not, the control module 12 obtains the particles within the item range as valid particles of the corresponding item to correct the particle cluster; the particle clusters can be corrected, the situation that the project in the prior art corresponds to two particle clusters is avoided, accuracy is improved, and implementation is easy.
Referring to fig. 7, fig. 7 is a schematic flowchart illustrating the first embodiment of step S102 in fig. 1. Step S102 of the above embodiment includes the steps of:
s701: the control module 12 selects any two of the scattered light detection data, the side scattered light detection data, and the classified fluorescence detection data to create a scattergram.
The control module 12 selects any two of the scattered light detection data, the side scattered light detection data and the classified fluorescence detection data to establish a scattergram, for example: the control module 12 creates a first scattergram based on the forward scatter detection data and the classified fluorescence detection data, as shown in fig. 3; the control module 12 establishes a second scattergram based on the side scatter detection data and the classified fluorescence detection data; the control module 12 creates a third scattergram based on the forward scatter detection data and the side scatter detection data, i.e., the scattergram includes the first scattergram, the second scattergram, and the third scattergram. In other embodiments of the present application, a person in the art may directly filter the detection data without setting the scatter diagram.
S702: the control module performs gaussian filtering, median filtering or mean filtering on the 12 scatter plot.
The control module 12 performs gaussian filtering, median filtering or mean filtering on the scatter diagram, for example, the control module 12 of this embodiment performs mean filtering on the first scatter diagram, the second scatter diagram and the third scatter diagram respectively.
S703: the control module 12 binarizes the filtered scatter diagram, performs an opening operation, and acquires a connected region to obtain a plurality of first clusters.
The control module 12 binarizes the filtered scatter diagram, performs an opening operation, and then obtains a connected region to obtain a plurality of first clusters. Wherein each connected region is the first particle cluster.
The control module 12 may obtain the connected region through depth-first traversal or breadth-first traversal, for example, the control module 12 obtains the connected region through depth-first traversal.
Optionally, in order to further remove the smaller connected region, the control module 12 is configured with a preset particle cluster area and a preset particle number, and calculates a first area and a first particle number of the first particle cluster; that is, the control module 12 calculates a first area and a first particle number of each first particle cluster, compares the first area of each first particle cluster with a preset particle cluster area, and compares the first particle number of each first particle cluster with a preset particle number. If the control module 12 determines that the first area is smaller than the preset particle cluster area or the first particle number is smaller than the preset particle number, the control module 12 deletes the corresponding first particle cluster, that is, removes the smaller connected region. If the control module 12 determines that the first area is larger than the preset particle cluster area and the first particle number is larger than the preset particle number, the control module 12 retains the corresponding first particle cluster to obtain the particle cluster corresponding to the item.
The control module 12 of this embodiment performs gaussian filtering, median filtering, or mean filtering on the scatter diagram; the control module 12 binarizes the filtered scatter diagram, performs opening operation, and acquires a connected region to obtain a plurality of first particle clusters, so that noise can be filtered, and the accuracy of the immunoassay analyzer is ensured.
S704: the control module 12 obtains the range of each first cluster to obtain a corresponding range array.
The control module 12 obtains a range of each first particle cluster from the plurality of first particle clusters obtained in step S703 to obtain a corresponding range array.
Referring to fig. 8, fig. 8 is a schematic flow chart of a second embodiment of the correction method of the present application. The correction method of the embodiment comprises the following steps:
s801: the control module 12 obtains the number of items of the immune joint inspection and obtains the inspection data from the inspection module 11.
S802: the control module 12 performs a cluster grasping process on the detection data to obtain a plurality of clusters.
S803: the control module 12 compares the number of all clusters with the number of items.
S804: if the control module 12 determines that the number of clusters is smaller than the number of items, the control module 12 corrects the clusters based on the median and the corresponding preset item range of each cluster.
Steps S801 to S804 are the same as steps S101 to S104 of the first embodiment, and are not described again here.
In step S803, the control module 12 compares the number of all clusters with the number of items. If the control module 12 determines that the number of clusters is smaller than the number of items, the process proceeds to step S804. If the control module 12 determines that the number of clusters is equal to the number of items, it proceeds to step S805. If the control module 12 determines that the number of clusters is greater than the number of items, the process proceeds to step S806.
S805: the control module 12 determines that the number of the clusters is equal to the number of the items, and the control module 12 determines that the median of at least two clusters is within the same item range, then the control module 12 retains the cluster with the largest area.
Wherein, the control module 12 determines that the number of the clusters is equal to the number of the items, and the control module 12 determines whether the median of at least two clusters is in the same item range; if not, the control module 12 does not need to correct the cluster. If so, the control module 12 determines that the same item has at least two clusters, and the control module 12 calculates the area of each cluster of the at least two clusters, retains the cluster with the largest area of the at least two clusters, and deletes the other clusters of the at least two clusters.
S806: the control module 12 determines that the number of clusters is greater than the number of items, and the control module 12 determines that the median of at least two clusters is within the same item range, so that the control module 12 retains the cluster with the largest area.
The control module 12 determines that the number of clusters is greater than the number of items, i.e. there are redundant clusters. Therefore, the control module 12 determines whether the median values of the at least two clusters are within the same project range; if not, the control module 12 does not need to correct the cluster. If so, the control module 12 determines that the same item has at least two clusters, and the control module 12 calculates the area of each cluster of the at least two clusters, retains the cluster with the largest area of the at least two clusters, and deletes the other clusters of the at least two clusters.
In this embodiment, the particle cluster having the largest area among the at least two particle clusters is retained, and the other particle clusters of the at least two particle clusters are deleted, so that the redundant particle clusters can be deleted, thereby improving the accuracy.
Optionally, in the present application, the multiple clusters are corrected by the above embodiment, and the control module 12 calculates the corresponding fluorescence intensity based on the fluorescence channel corresponding to each cluster; the control module 12 obtains a plurality of modified particle clusters and bases the fluorescence channel corresponding to each modified particle cluster; the control module 12 calculates the corresponding fluorescence intensity according to the fluorescence channel. The control module 12 compares the fluorescence intensity with a preset calibration curve to obtain the item concentration corresponding to the particle cluster.
Optionally, the control module 12 selects the forward scatter detection data and the classified fluorescence detection data as a first set of data, selects the side scatter detection data and the classified fluorescence detection data as a second set of data, and selects the forward scatter detection data and the side scatter detection data as a third set of data. In an embodiment, the control module 12 sequentially filters the first group of data, the third group of data, and the second group of data, and the filtering process is the same as steps S701 to S703, which is not described herein again. The filtering of the remaining outliers near each cluster is accomplished by the control module 12 filtering the side scatter detection data and the sorted fluorescence detection counts.
In one embodiment, the control module 12 sequentially filters the first and third sets of data. The filtering process is the same as steps S701 to S703, and is not described herein again.
In one embodiment, the control module 12 sequentially filters the second and third sets of data. The filtering process is the same as steps S701 to S703, and is not described herein again.
In one embodiment, the control module 12 sequentially filters the second set of data, the third set of data, and the first set of data. The filtering process is the same as steps S701 to S703, and is not described herein again.
The application also provides an immunoassay analyzer, as shown in fig. 2, the immunoassay analyzer of the present embodiment includes a detection module 11 and a control module 12, the control module 12 is connected to the detection module 11, and the control module 12 is configured to control the detection module 11 to perform multiple immunodetection tests on a sample; the sample may be serum or whole blood.
The control module 12 is configured to obtain the quantity of items for the immune joint inspection, and obtain the inspection data from the inspection module 11. The control module 12 is configured to perform a bolus processing on the detection data to obtain a plurality of particle boluses. The control module 12 is used to compare the number of all clusters with the number of items. The control module 12 is configured to determine that the number of clusters is smaller than the number of items, and the control module 12 corrects the clusters based on the median of each cluster and the corresponding preset item range.
Optionally, the control module 12 is configured to obtain a first median value of each particle group on the forward scattered light and a second median value on the classified fluorescence; the control module 12 is configured to determine whether the first median is located in the corresponding forward scattered light range, and whether the second median is located in the corresponding classified fluorescence range; the control module 12 is configured to obtain particles located in the item range as valid particles of the corresponding item to correct the particle swarm; the control module 12 is configured to save the item range to the range array of the corresponding particle swarm.
Optionally, the control module 12 is configured to select any two of the scattered light detection data, the side scattered light detection data, and the classified fluorescence detection data to create a scattergram. The control module is used for carrying out Gaussian filtering, median filtering or mean filtering on the 12 scatter diagram. The control module 12 is configured to binarize the filtered scattergram, perform an opening operation, and acquire a connected region to obtain a plurality of first clusters. The control module 12 is configured to obtain a range of each first particle cluster to obtain a corresponding range array.
Optionally, the control module 12 is configured to determine that the number of clusters is equal to the number of items, and if the control module 12 determines that the median of at least two clusters is within the same item range, the control module 12 retains the cluster with the largest area.
Optionally, the control module 12 is configured to determine that the number of the particle clusters is greater than the number of the items, and if the control module 12 determines that the median of at least two particle clusters is within the same item range, the control module 12 retains the particle cluster with the largest area.
To sum up, the immunoassay analyzer of the present application includes a detection module 11 and a control module 12, where the detection module 11 is used to perform multiple detections of immune joint inspection on a sample, where the control module 12 obtains the number of items of immune joint inspection, and obtains detection data from the detection module 11; the control module 12 performs cluster grabbing processing on the detection data to obtain a plurality of clusters; the control module 12 compares the number of all clusters with the number of items; if the control module 12 determines that the number of clusters is smaller than the number of items, the control module 12 corrects the clusters based on the median and the corresponding preset item range of each cluster. The particle clusters are corrected through the control module 12 based on the median value of each particle cluster and the corresponding and preset project range, the problem that the project in the prior art has two particle clusters can be solved, and the accuracy is improved.
The above description is only for the purpose of illustrating embodiments of the present application and is not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application or are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.

Claims (10)

1. A correction method is applied to an immunoassay analyzer, the immunoassay analyzer comprises a detection module and a control module, the detection module is used for carrying out a plurality of detections of an immune joint test on a sample, and the correction method comprises the following steps:
the control module acquires the quantity of items of the immune joint inspection and acquires detection data from the detection module;
the control module performs cluster grabbing processing on the detection data to obtain a plurality of clusters;
the control module compares the number of all clusters with the number of items;
and the control module judges that the number of the particle clusters is smaller than the number of the items, and corrects the particle clusters based on the median value of each particle cluster and the corresponding preset item range.
2. The method of claim 1, wherein the detection data includes forward scatter detection data, side scatter detection data, and classified fluorescence detection data, and the step of the control module modifying each of the clusters based on the median value of the cluster and a corresponding predetermined range of items comprises:
the control module acquires a first median value of each particle group on forward scattered light and a second median value of each particle group on classified fluorescence;
wherein the range of items includes a forward scattered light range and a classified fluorescence range corresponding to the particle cluster.
3. The method according to claim 2, wherein the step of the control module correcting the particle clusters based on the median value of each particle cluster and the corresponding preset item range comprises:
the control module judges whether the first median value is located in the corresponding forward scattering light range or not and whether the second median value is located in the corresponding classified fluorescence range or not;
if not, the control module acquires the particles in the item range as effective particles of the corresponding item so as to correct the particle cluster.
4. The correction method according to claim 3, wherein after the step of the control module acquiring the particles within the range of the item as valid particles of the corresponding item, the correction method further comprises:
and the control module stores the item range to the range array of the corresponding particle swarm.
5. The correction method according to claim 2, wherein the step of the control module performing a bolus processing on the detection data to obtain a plurality of boluses comprises:
the control module selects any two of the scattered light detection data, the side scattered light detection data and the classified fluorescence detection data to establish a scatter diagram.
6. The correction method according to claim 5, wherein after the step of the control module selecting any two of the scattered light detection data, the side scattered light detection data and the classified fluorescence detection data to create a scattergram, the correction method further comprises:
the control module performs Gaussian filtering, median filtering or mean filtering on the scatter diagram;
the control module is used for carrying out binarization on the filtered scatter diagram, carrying out opening operation and obtaining a communicated region so as to obtain a plurality of first particle clusters;
and the control module acquires the range of each first particle cluster to obtain a corresponding range array.
7. The correction method according to any one of claims 1 to 6, wherein the step of the control module comparing the number of all clusters with the number of items comprises:
if the control module judges that the number of the particle clusters is larger than the number of the items, the control module judges whether the median values of all the particle clusters are located in the same item range;
and the control module judges that the median of at least two particle clusters is in the same item range, and then the control module reserves the particle cluster with the largest area.
8. The correction method according to claim 7, wherein the step of the control module comparing the number of all clusters with the number of items comprises:
and the control module judges that the number of the particle clusters is equal to the number of the items, and the control module judges that the median of at least two particle clusters is in the same item range, so that the control module reserves the particle cluster with the largest area.
9. The correction method according to claim 7, characterized in that the correction method further comprises:
the control module calculates corresponding fluorescence intensity based on the fluorescence channel corresponding to each particle cluster;
and the control module compares the fluorescence intensity with a preset calibration curve to obtain the item concentration corresponding to the particle cluster.
10. An immunoassay analyzer, comprising a detection module and a control module, wherein the detection module is used for carrying out a plurality of detections on a sample by an immune joint inspection, and the immunoassay analyzer comprises:
the control module is used for acquiring the quantity of items of the immune joint inspection and acquiring the detection data from the detection module;
the control module is used for carrying out group grabbing processing on the detection data to obtain a plurality of particle groups;
the control module is used for comparing the quantity of all particle clusters with the quantity of the items;
and the control module is used for judging that the number of the particle clusters is smaller than the number of the items, and correcting the particle clusters based on the median value of each particle cluster and the corresponding preset item range.
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